From Demand Signal to Deployed Rack: Building AI-Driven Capacity Planning Systems

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While the chatter about AI is incessant, many people are unaware of the intricacies of effective AI deployment at data centers. Yet, it's exactly this architecture that provides the scaffolding for tools such as ChatGPT, Nano Banana, and Copilot. If you're curious about how AI is operationalized on a large-scale and the specific hardware pieces that make it possible, then you are in luck. Tuesday, April 20th, join Nainsi Jain as she provides a technical walkthrough of the end-to-end process of scaling hyperscale data center infrastructure — from interpreting customer demand signals to physical rack deployment — and how AI-driven capacity planning is making that process faster and more reliable


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  • From Demand Signal to Deployed Rack: Building AI-Driven Capacity Planning Systems

  • Starts 16 March 2026 04:00 AM UTC
  • Ends 20 April 2026 04:00 AM UTC
  • No Admission Charge

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From Demand Signal to Deployed AI presented by Nainsi Jain

 

Nainsi Jain is a Senior Technical Program Manager at Amazon Web Services, where she is leading the development of a six-product enterprise platform that has fundamentally transformed global data center network capacity delivery eliminating 21 legacy tools and achieved 40% operational efficiencies, and avoidance of $95 million in cost within three years of global launch. Managing programs of high complexity, Nainsi aligns 200+ contributors across software engineering, infrastructure delivery, supply chain, and finance across multiple continents consistently delivering reduction in infrastructure lead times and SLAs.

With 16+ years of progressive leadership spanning technical program management, data analytics, supply chain transformation, and international business operations across the United States and India, Nainsi brings a rare combination of technical depth, strategic vision, and operational rigor to every program she leads. She holds a Master’s in Business Administration, a Master of Science in Data Science and a Master of Science in Global Logistics. She is an IEEE Member and active member of the IEEE Computer Society, Women in Engineering, and Technology and Engineering Management Society, recognized as a thought leader, invited speaker, and judge within the global engineering community.